Google DeepMind Releases Qwen 3: What the Benchmarks Actually Show
Notes from the teams shipping long context to real users.
For most of the last year, the conversation around computer-use agents has been louder than the evidence. That is starting to change.
Booking.com has been quietly running lead qualification through Granola for months. The results are unglamorous and, for that reason, more interesting than another benchmark chart.
Eval harnesses, once an afterthought, are becoming the most important piece of code in many AI projects. Databricks's team treats theirs the way an SRE team treats a runbook.
Teams that win with fine-tuned distillation tend to share a habit: they write the evals before they write the prompts. Everything else follows from that.
Inside Figma, the rollout looked less like a moonshot and more like a slow migration. A pilot, a champion, a quiet expansion, a budget line.
Inside HubSpot, the rollout looked less like a moonshot and more like a slow migration. A pilot, a champion, a quiet expansion, a budget line.
Teams that win with long-context workflows tend to share a habit: they write the evals before they write the prompts. Everything else follows from that.
None of this guarantees a clean story. xAI could ship a model next month that rearranges the assumptions in this piece. But the direction of travel, for now, is clear enough to plan around.